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Particle swarm optimization is proposed to optimize the particle filter in order to Travel out the well-known particle impoverishment and dependency problem. Through particle swarm optimization, particle samples are moved to neighbor higher likelihood areas. In this way, it can obtain more approximate to the true posterior probability density function. Meanwhile, the number of particle sample reducing...
A systematical approach that can synthesize system contingencies into probabilistic PSS design is developed. A critical contingency screening is first conducted by a ranking of contingencies according to a probabilistic small signal stability index. A multi-objective optimization model is formulated to seek satisfactory system damping performance under both pre-contingency and post-contingency situations...
Based on the geometrical theory of the reliability index and taking advantage of an improved particle swarm optimization with simple parameter setting and high convergence speed, a movement precision reliability computation method of the main motion of internal combustion engine is presented. The proposed method avoids the partial derivatives calculation in the performance function, and it is suitable...
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